Modelling the Effects of Electrical Coupling between Unmyelinated Axons of Brainstem Neurons Controlling Rhythmic Activity: Electrical Coupling via Unmyelinated Axons

Michael Hull, Stephen Soffe, David J Willshaw, Alan Roberts

Research output: Contribution to journalArticle (Academic Journal)peer-review

11 Citations (Scopus)

Abstract

Gap junctions between fine unmyelinated axons can electrically couple groups of brain neurons
to synchronise firing and contribute to rhythmic activity. To explore the distribution and
significance of electrical coupling, we modelled a well analysed, small population of brainstem
neurons which drive swimming in young frog tadpoles. A passive network of 30 multicompartmental
neurons with unmyelinated axons was used to infer that: axon-axon gap
junctions close to the soma gave the best match to experimentally measured coupling
coefficients; axon diameter had a strong influence on coupling; most neurons were coupled
indirectly via the axons of other neurons. When active channels were added, gap junctions
could make action potential propagation along the thin axons unreliable. Increased sodium
and decreased potassium channel densities in the initial axon segment improved action potential
propagation. Modelling suggested that the single spike firing to step current injection
observed in whole-cell recordings is not a cellular property but a dynamic consequence of
shunting resulting from electrical coupling. Without electrical coupling, firing of the population
during depolarising current was unsynchronised; with coupling, the population showed
synchronous recruitment and rhythmic firing. When activated instead by increasing levels of
modelled sensory pathway input, the population without electrical coupling was recruited incrementally
to unpatterned activity. However, when coupled, the population was recruited
all-or-none at threshold into a rhythmic swimming pattern: the tadpole “decided” to swim.
Modelling emphasises uncertainties about fine unmyelinated axon physiology but, when informed
by biological data, makes general predictions about gap junctions: locations close to
the soma; relatively small numbers; many indirect connections between neurons; cause of
action potential propagation failure in fine axons; misleading alteration of intrinsic firing
properties. Modelling also indicates that electrical coupling within a population can synchronize
recruitment of neurons and their pacemaker firing during rhythmic activity.
Original languageEnglish
Article numbere1004240
Pages (from-to)1-26
Number of pages26
JournalPLoS Computational Biology
Volume11
Issue number5
DOIs
Publication statusPublished - 2015

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